Search results for "Python for Generative AI"
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Generative AI and Digital Forensics
In today’s world, cybersecurity attacks and security breaches are becoming the norm. Unfortunately, we are not immune to it, and any individual and entity is at dire risk. The best and only thing that we can do is to mitigate the risks as much as much as possible so that they do not happen at all. But even when a security breach does indeed happen, the immediate reaction is to contain it so that it does not penetrate further into the IT/Network Infrastructure. From there, mission-critical processes need to be restored, until the business can resume a normal state of operations, like it was before the security breach.But another key step here is to investigate how and why the security breach happened in the first place. The best to do this is through what is known as “Digital Forensics”. This is where specially trained Digital Forensics Investigators collect and comb through every piece of evidence to determine this. Eventually, the goal is then to use this evidence in a court of law so the cyberattacker can be made to answer to their crime and eventually be brought to justice.However, the area of digital forensics is a large one, and many topics around it can be covered. Also, generative AI is being used to not only help in the analysis of the evidence, but also to help automate the Digital Forensics software packages that are available today. Therefore, in this book, the following is covered:Examples of security breaches, and overview into Digital ForensicsHow Digital Forensics can be used to investigate the loss or theft of dataAn introduction to the SQL Server DatabaseA review of the SQL Injection AttackHow generative AI can be used in Digital Forensics
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Blueprints for Text Analytics using Python
Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving complex challenges. But it's not always clear which NLP tools or libraries would work for a business's needs, or which techniques you should use and in what order.This practical book provides data scientists and developers with blueprints for best practice solutions to common tasks in text analytics and natural language processing. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler provide real-world case studies and detailed code examples in Python to help you get started quickly.Extract data from APIs and web pagesPrepare textual data for statistical analysis and machine learningUse machine learning for classification, topic modeling, and summarizationExplain AI models and classification resultsExplore and visualize semantic similarities with word embeddingsIdentify customer sentiment in product reviewsCreate a knowledge graph based on named entities and their relations
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Kivy: Interactive Applications in Python
into the world of Kivy.This book is aimed at Python developers who are familiar with Python and have a good understanding of concepts like inheritance, classes, and instances. No previous experience of Kivy is required, though some knowledge of event handling, scheduling, and user interfaces, in general, would boost your learning.
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Deep Generative Models, and Data Augmentation, Labelling, and Imperfections
This book constitutes the refereed proceedings of the First MICCAI Workshop on Deep Generative Models, DG4MICCAI 2021, and the First MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2021, held in conjunction with MICCAI 2021, in October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic.DG4MICCAI 2021 accepted 12 papers from the 17 submissions received. The workshop focusses on recent algorithmic developments, new results, and promising future directions in Deep Generative Models. Deep generative models such as Generative Adversarial Network (GAN) and Variational Auto-Encoder (VAE) are currently receiving widespread attention from not only the computer vision and machine learning communities, but also in the MIC and CAI community.For DALI 2021, 15 papers from 32 submissions were accepted for publication. They focus on rigorous study of medical data related to machine learning systems.
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Python for Engineers and Scientists
The text focuses on the basics of Python programming fundamentals and introduction to present-day applications in technology and the upcoming state-of-art trends in a comprehensive manner. The text is based on Python 3.x and it covers the fundamentals of Python with object-oriented concepts having numerous worked-out examples. It provides a learning tool for the students of beginner level as well as for researchers of advanced level. Each chapter contains additional examples that explain the usage of methods/functions discussed in the chapter. It provides numerous programming examples along with their outputs.The book:Includes programming tips to highlight the important concepts and help readers avoid common programming errorsProvides programming examples along with their outputs to ensure the correctness and help readers in mastering the art of writing efficient Python programsContains MCQs with their answers; conceptual questions and programming questions; and solutions to some selected programming questions, for every chapterDiscusses applications like time zone converter and password generators at the endCovers fundamental of Python up to object oriented concepts including regular expressionThe book offers a simple and lucid treatment of concepts supported with illustrations for easy understanding, provides numerous programming examples along with their outputs, and includes programming tips to highlight the important concepts. It will be a valuable resource for senior undergraduate, graduate students, and professionals in the fields of electrical engineering, electronics and communication engineering, and computer engineering.
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Generative AI with SAP and Amazon Bedrock
Explore Generative AI and understand its key concepts, architecture, and tangible business use cases. This book will help you develop the skills needed to use SAP AI Core service features available in the SAP Business Technology Platform.You’ll examine large language model (LLM) concepts and gain the practical knowledge to unleash the best use of Gen AI. As you progress, you’ll learn how to get started with your own LLM models and work with Generative AI use cases. Additionally, you’ll see how to take advantage Amazon Bedrock stack using AWS SDK for ABAP.To fully leverage your knowledge, Generative AI with SAP and Amazon Bedrock offers practical step-by-step instructions for how to establish a cloud SAP BTP account model and create your first GenAIartifacts. This work is an important prerequisite for those who want to take full advantage of generative AI with SAP.What You Will LearnMaster the concepts and terminology of artificial intelligence and GenAIUnderstand opportunities and impacts for different industries with GenAIBecome familiar with SAP AI Core, Amazon Bedrock, AWS SDK for ABAP and develop your firsts GenAI projectsAccelerate your development skillsGain more productivity and time implementing GenAI use casesWho this Book Is ForAnyone who wants to learn about Generative AI for Enterprise and SAP practitioners who want to take advantage of AI within the SAP ecosystem to support their systems and workflows.
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Theory Of Cognitive Chasms: Delivering Business Value From Genai
This comprehensive book provides a research-backed framework explaining why GenAI adoptions routinely fail to deliver business value across enterprises. Based on a grounded theory approach, it identifies four major failure modes, or the Cognitive Chasms, that represent exponential risks to adoption.The scope details the complete causal framework, including antecedents, moderators, consequents and the core mediator, Cognitive Decision-Making, which marks the boundary condition of successful GenAI adoptions. The volume also proposes a Multistage Scaling Strategy (a dynamic roadmap for enterprise adoption) and essential Cognitive Mindsets (attitudes and beliefs integral to GenAI adoption) to successfully cross the cognitive chasms.Serving as a prescriptive field manual, this useful handbook benefits professionals, researchers, academics, postgraduate and graduate students in the fields of AI, technology/information management, organization behavior and business strategy and management.
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